基于dft的共价有机框架在吸附、光电、清洁能源存储和气体传感器应用中的评价。

IF 2.5 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Abhay P. Srivastava, Brijesh K. Pandey
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引用次数: 0

摘要

背景:共价有机框架(COFs)是由强共价键结合在一起的轻原子组成的框架,作为可再生能源和气体捕获等应用的潜在材料,正引起人们的兴趣。我们使用VASP代码中实现的密度泛函理论(DFT)计算来查看2D和3D COFs。我们系统地分析了各种性能,包括结构稳定性、声子色散、电子结构、态密度、吸附行为和力学性能。为了获得更好的准确性,我们考虑了范德华相互作用,甚至使用了混合泛函。我们发现,3D COFs通常具有更高的机械强度,并且在大多数情况下具有更好的气体吸附,这似乎来自于它们相互连接的孔隙结构。另一方面,二维COFs表现出增强的π电子离域和约2.5 eV的直接带隙,这可能有助于传感器和光电子学。声子分析验证了两种结构的动力稳定性。最终,这些结果强调了维度在为能源和电子应用量身定制COF特性方面的重要性。方法:利用维也纳从头算模拟包(VASP)中的密度泛函理论(DFT)进行第一性原理模拟。为了考虑交换相关效应,我们在Perdew-Burke-Ernzerhof (PBE)公式中使用了广义梯度近似(GGA),并且我们还使用了投影增强波(PAW)伪势。引入混合泛函(HSE06)和DFT-D3范德华校正来提高带隙预测的精度。平面波截止点设置为500 eV进行计算,采用3 × 3 × 1 (2D)和2 × 2 × 2 (3D)网格的Monkhorst-Pack k点网格。评估了结构优化、能带结构、总DOS和预计DOS、吸附能和电荷转移(使用Bader分析)。利用电子定位函数(ELF)和电荷密度差(Δρ)可视化来评估键合特征。利用Phonopy包计算声子色散,从而确定了COFs的动态稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

DFT-based evaluation of covalent organic frameworks for adsorption, optoelectronic, clean energy storage, and gas sensor applications

DFT-based evaluation of covalent organic frameworks for adsorption, optoelectronic, clean energy storage, and gas sensor applications

Context

Covalent Organic Frameworks (COFs), which are frameworks composed of light atoms held together by strong covalent bonds, are generating interest as potential materials for applications such as renewable energy and gas capture. We employed Density Functional Theory (DFT) calculations, as implemented in the VASP code, to look at both 2D and 3D COFs. We systematically analyzed various properties, including structural stability, phonon dispersion, electronic structures, density of states, adsorption behavior, and mechanical properties. To get better accuracy, we took into account van der Waals interactions and even used hybrid functionals. What we found was that 3D COFs generally exhibit greater mechanical strength and, in most cases, better gas adsorption, which seems to come from their interconnected pore structures. On the other hand, 2D COFs exhibit enhanced π-electron delocalization and direct band gaps of approximately 2.5 eV, which may be helpful in sensors and optoelectronics. Phonon analyses verified the dynamical stability of both structures. Ultimately, these results underscore the importance of dimensionality in tailoring COF properties for energy and electronic applications.

Method

First-principles simulations were performed using Density Functional Theory (DFT) within the Vienna Ab initio Simulation Package (VASP). To account for exchange–correlation effects, we employed the Generalised Gradient Approximation (GGA) in the Perdew–Burke–Ernzerhof (PBE) formulation, and we also utilised projector-augmented wave (PAW) pseudopotentials. Hybrid functional (HSE06) and DFT-D3 van der Waals corrections were introduced to improve the accuracy of our band gap prediction. The plane-wave cutoffs were set at 500 eV for the calculations, and Monkhorst–Pack k-point meshes were used with a 3 × 3 × 1 (2D) and 2 × 2 × 2 (3D) grid. Evaluated were structural optimisations, band structures, total and projected DOS, adsorption energies, and charge transfer (using Bader analysis). Assessment of bonding features utilised the Electron Localisation Function (ELF) and charge density difference (Δρ) visualisations. The Phonopy package was used to calculate Phonon dispersions and thus confirm the dynamic stability of the COFs.

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来源期刊
Journal of Molecular Modeling
Journal of Molecular Modeling 化学-化学综合
CiteScore
3.50
自引率
4.50%
发文量
362
审稿时长
2.9 months
期刊介绍: The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling. Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry. Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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